基于多特征提取的语音情感分类  

Speech emotion classification based on multi-feature extraction

作　　者：张宇哲 郭传杰 靳淑雅 马驰远 苏煜 陶智勇 ZHANG Yuzhe;GUO Chuanjie;JIN Shuya;MA Chiyuan;SU Yu;TAO Zhiyong(Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education,Guilin University of Electronic Technology,Guilin 541004,Guangxi,China;Guilin University of Electronic Technology,Beihai 536000,Guangxi,China)

机构地区：[1]桂林电子科技大学认知无线电与信息处理教育部重点实验室,广西桂林541004 [2]桂林电子科技大学,广西北海536005

出　　处：《声学技术》2025年第2期261-269,共9页Technical Acoustics

基　　金：广西自然科学基金项目(2021GXNSFDA075006);国家自然科学基金项目(12064005)。

摘　　要：情感识别是计算机对人类情感感知过程的模拟,具有重要的研究意义和应用价值。传统的语音识别系统通常使用单一的特征提取方法,但这些方法有时会丢失语音情感信号中的重要信息,导致识别错误。因此,文章基于改进的完全集成噪声自适应经验模式分解,提出了一种组合多特征提取方法来分类无语义情感语音信号。首先,利用基于改进的完全集成噪声自适应经验模式分解将一维情感语音信号分解得到多个内禀模式;然后,提取每个内禀模式的均值、方差、峰度、偏度、能量、中心频率、峰值幅度和排列熵等特征;最后,通过这些特征对愤怒、快乐、悲伤和无情感四种情感进行分类。研究表明,该方法在通过支持向量机8∶2的模型训练后,得到了88.52%的平均识别率,可为情感语音信号的识别工作提供重要参考。Emotion recognition is a type of computer simulation for human emotion perception process,which is significant in research and applications.Traditional speech recognition systems usually employ a single feature extraction method,which sometimes loses important information from speech emotion signals.Therefore,based on the improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN),a combined multi-feature extraction method to classify semantically independent speech emotion signals is proposed in this paper.ICEEMDAN decomposes one-dimensional speech signals into multiple intrinsic modes,and then extracts characteristics such as energy intensity,average,variance,kurtosis,skewness,center frequency,peak amplitude,permutation entropy from each decomposed mode.Finally,four emotions such as anger,happiness,sadness,and no emotion are classified.The results show that the proposed method achieves an average recognition rate of 88.52%after training with an 8∶2 model of the support vector machine(SVM).It can provide an important reference for speech emotion recognition.

关 键 词：情感语音 自适应经验模态分解 特征提取 支持向量机 

分 类 号：B845.2[哲学宗教—心理学]